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Record W2127139510 · doi:10.1186/1479-5876-9-92

Trauma is danger

2011· review· en· W2127139510 on OpenAlexaff
Paul F. Hwang, Nancy Porterfield, Dylan Pannell, Thomas A. Davis, Eric A. Elster

Bibliographic record

VenueJournal of Translational Medicine · 2011
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsCanadian Armed ForcesUniversity of Toronto
FundersOffice of Naval ResearchU.S. NavyBureau of Medicine and SurgeryHenry M. Jackson Foundation
KeywordsContext (archaeology)Immune systemEffectorMedicineInnate immune systemInflammatory responseImmunologyIntensive care medicineFunction (biology)NeuroscienceBioinformaticsInflammationBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Trauma is one of the leading causes of death in young adult patients. Many pre-clinical and clinical studies attempt to investigate the immunological pathways involved, however the true mediators remain to be elucidated. Herein, we attempt to describe the immunologic response to systemic trauma in the context of the Danger model. DATA SOURCES: A literature search using PubMed was used to identify pertinent articles describing the Danger model in relation to trauma. CONCLUSIONS: Our knowledge of Danger signals in relation to traumatic injury is still limited. Danger/alarmin signals are the most proximal molecules in the immune response that have many possibilities for effector function in the innate and acquired immune systems. Having a full understanding of these molecules and their pathways would give us the ability to intervene at such an early stage and may prove to be more effective in blunting the post-injury inflammatory response unlike previously failed cytokine experiments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.076
GPT teacher head0.337
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2011
Admission routes1
Has abstractyes

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